Contextual portrait detection

A frequently occurring problem in face verification in Jumio is that stock face detectors find multiple faces in the input image. The decision which one should be selected for the face verification step is not clear. Common reasons being, users submitting a single image with both selfie and document id. There can be other people, paintings, posters or television screens in the background.
Users may upload the selfie and the document picture in reverse order, etc. A human can easily select the right face but for an automated selection we need additional signals from the face detector – the context in which the face was detected. The goal of this project is to build a system using Artificial Intelligence that can provide additional context along with the detected faces in order to increase the efficiency of the existing face verification systems.

Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

Jumio

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Montréal

Program: